/ Check-in [4847c6cb]
Login

Many hyperlinks are disabled.
Use anonymous login to enable hyperlinks.

Overview
Comment:Change the weighting of binary searches on tables to 1/10th the cost of a search on an index. Change the assumed reduction in search space from a indexed range constraint from 1/3rd to 1/4th. Do not let the estimated number of rows drop below 1.
Downloads: Tarball | ZIP archive | SQL archive
Timelines: family | ancestors | descendants | both | stat2-enhancement
Files: files | file ages | folders
SHA1: 4847c6cb71423248b186ab7842b97c83e2f5fefd
User & Date: drh 2011-01-28 01:57:41
Context
2011-01-28
03:13
Reactivate the analyze5.test script. Closed-Leaf check-in: a2a9f640 user: drh tags: stat2-enhancement
01:57
Change the weighting of binary searches on tables to 1/10th the cost of a search on an index. Change the assumed reduction in search space from a indexed range constraint from 1/3rd to 1/4th. Do not let the estimated number of rows drop below 1. check-in: 4847c6cb user: drh tags: stat2-enhancement
2011-01-24
17:46
Restructuring and generalizing analyze5.test. The whole script is currently disabled and will need to be reenabled prior to merging with trunk. check-in: 31fcc706 user: drh tags: stat2-enhancement
Changes
Hide Diffs Unified Diffs Ignore Whitespace Patch

Changes to src/where.c.

2417
2418
2419
2420
2421
2422
2423
2424
2425
2426
2427
2428
2429
2430
2431
2432
2433
....
2494
2495
2496
2497
2498
2499
2500
2501
2502
2503
2504
2505
2506
2507
2508
2509
....
2632
2633
2634
2635
2636
2637
2638
2639
2640
2641
2642
2643
2644
2645
2646
2647
2648
2649
2650
2651
....
2656
2657
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
....
2699
2700
2701
2702
2703
2704
2705
2706
2707


2708
2709
2710
2711
2712
2713
2714
2715
2716
2717
2718


2719
2720
2721
2722
2723
2724
2725
....
2729
2730
2731
2732
2733
2734
2735

2736
2737
2738
2739
2740
2741
2742
2743
2744


2745
2746
2747
2748
2749
2750
2751
....
2761
2762
2763
2764
2765
2766
2767
2768


2769
2770
2771
2772
2773
2774
2775
2776
2777
2778
2779
2780
2781
2782
2783
2784
2785
2786

2787
2788
2789
2790
2791


2792
2793
2794
2795
2796
2797
2798
2799
2800
2801
2802
2803
2804
2805
2806
2807
2808
2809
....
2814
2815
2816
2817
2818
2819
2820
2821
2822
2823
2824
2825
2826
2827
2828
2829
2830
....
2919
2920
2921
2922
2923
2924
2925

2926
2927
2928

2929





2930

2931
2932






2933
2934





2935








2936
2937
2938
2939
2940
2941
2942
....
2983
2984
2985
2986
2987
2988
2989
2990




2991
2992
2993
2994
2995
2996
2997
** value of 1 indicates that the proposed range scan is expected to visit
** approximately 1/100th (1%) of the rows selected by the nEq equality
** constraints (if any). A return value of 100 indicates that it is expected
** that the range scan will visit every row (100%) selected by the equality
** constraints.
**
** In the absence of sqlite_stat2 ANALYZE data, each range inequality
** reduces the search space by 2/3rds.  Hence a single constraint (x>?)
** results in a return of 33 and a range constraint (x>? AND x<?) results
** in a return of 11.
*/
static int whereRangeScanEst(
  Parse *pParse,       /* Parsing & code generating context */
  Index *p,            /* The index containing the range-compared column; "x" */
  int nEq,             /* index into p->aCol[] of the range-compared column */
  WhereTerm *pLower,   /* Lower bound on the range. ex: "x>123" Might be NULL */
  WhereTerm *pUpper,   /* Upper bound on the range. ex: "x<455" Might be NULL */
................................................................................
#else
  UNUSED_PARAMETER(pParse);
  UNUSED_PARAMETER(p);
  UNUSED_PARAMETER(nEq);
#endif
  assert( pLower || pUpper );
  *piEst = 100;
  if( pLower && (pLower->wtFlags & TERM_VNULL)==0 ) *piEst /= 3;
  if( pUpper ) *piEst /= 3;
  return rc;
}

#ifdef SQLITE_ENABLE_STAT2
/*
** Estimate the number of rows that will be returned based on
** an equality constraint x=VALUE and where that VALUE occurs in
................................................................................
  sqlite3ValueFree(pVal);
  return rc;
}
#endif /* defined(SQLITE_ENABLE_STAT2) */


/*
** Find the query plan for accessing a particular table.  Write the
** best query plan and its cost into the WhereCost object supplied as the
** last parameter.
**
** The lowest cost plan wins.  The cost is an estimate of the amount of
** CPU and disk I/O need to process the request using the selected plan.
** Factors that influence cost include:
**
**    *  The estimated number of rows that will be retrieved.  (The
**       fewer the better.)
**
**    *  Whether or not sorting must occur.
**
................................................................................
** the SQL statement, then this function only considers plans using the 
** named index. If no such plan is found, then the returned cost is
** SQLITE_BIG_DBL. If a plan is found that uses the named index, 
** then the cost is calculated in the usual way.
**
** If a NOT INDEXED clause (pSrc->notIndexed!=0) was attached to the table 
** in the SELECT statement, then no indexes are considered. However, the 
** selected plan may still take advantage of the tables built-in rowid
** index.
*/
static void bestBtreeIndex(
  Parse *pParse,              /* The parsing context */
  WhereClause *pWC,           /* The WHERE clause */
  struct SrcList_item *pSrc,  /* The FROM clause term to search */
  Bitmask notReady,           /* Mask of cursors not available for indexing */
................................................................................

  if( pSrc->pIndex ){
    /* An INDEXED BY clause specifies a particular index to use */
    pIdx = pProbe = pSrc->pIndex;
    wsFlagMask = ~(WHERE_ROWID_EQ|WHERE_ROWID_RANGE);
    eqTermMask = idxEqTermMask;
  }else{
    /* There is no INDEXED BY clause.  Create a fake Index object to
    ** represent the primary key */


    Index *pFirst;                /* Any other index on the table */
    memset(&sPk, 0, sizeof(Index));
    sPk.nColumn = 1;
    sPk.aiColumn = &aiColumnPk;
    sPk.aiRowEst = aiRowEstPk;
    sPk.onError = OE_Replace;
    sPk.pTable = pSrc->pTab;
    aiRowEstPk[0] = pSrc->pTab->nRowEst;
    aiRowEstPk[1] = 1;
    pFirst = pSrc->pTab->pIndex;
    if( pSrc->notIndexed==0 ){


      sPk.pNext = pFirst;
    }
    pProbe = &sPk;
    wsFlagMask = ~(
        WHERE_COLUMN_IN|WHERE_COLUMN_EQ|WHERE_COLUMN_NULL|WHERE_COLUMN_RANGE
    );
    eqTermMask = WO_EQ|WO_IN;
................................................................................
  /* Loop over all indices looking for the best one to use
  */
  for(; pProbe; pIdx=pProbe=pProbe->pNext){
    const unsigned int * const aiRowEst = pProbe->aiRowEst;
    double cost;                /* Cost of using pProbe */
    double nRow;                /* Estimated number of rows in result set */
    int rev;                    /* True to scan in reverse order */

    int wsFlags = 0;
    Bitmask used = 0;

    /* The following variables are populated based on the properties of
    ** scan being evaluated. They are then used to determine the expected
    ** cost and number of rows returned.
    **
    **  nEq: 
    **    Number of equality terms that can be implemented using the index.


    **
    **  nInMul:  
    **    The "in-multiplier". This is an estimate of how many seek operations 
    **    SQLite must perform on the index in question. For example, if the 
    **    WHERE clause is:
    **
    **      WHERE a IN (1, 2, 3) AND b IN (4, 5, 6)
................................................................................
    **
    **    If there exists a WHERE term of the form "x IN (SELECT ...)", then 
    **    the sub-select is assumed to return 25 rows for the purposes of 
    **    determining nInMul.
    **
    **  bInEst:  
    **    Set to true if there was at least one "x IN (SELECT ...)" term used 
    **    in determining the value of nInMul.


    **
    **  estBound:
    **    An estimate on the amount of the table that must be searched.  A
    **    value of 100 means the entire table is searched.  Range constraints
    **    might reduce this to a value less than 100 to indicate that only
    **    a fraction of the table needs searching.  In the absence of
    **    sqlite_stat2 ANALYZE data, a single inequality reduces the search
    **    space to 1/3rd its original size.  So an x>? constraint reduces
    **    estBound to 33.  Two constraints (x>? AND x<?) reduce estBound to 11.
    **
    **  bSort:   
    **    Boolean. True if there is an ORDER BY clause that will require an 
    **    external sort (i.e. scanning the index being evaluated will not 
    **    correctly order records).
    **
    **  bLookup: 
    **    Boolean. True if for each index entry visited a lookup on the 
    **    corresponding table b-tree is required. This is always false 

    **    for the rowid index. For other indexes, it is true unless all the 
    **    columns of the table used by the SELECT statement are present in 
    **    the index (such an index is sometimes described as a covering index).
    **    For example, given the index on (a, b), the second of the following 
    **    two queries requires table b-tree lookups, but the first does not.


    **
    **             SELECT a, b    FROM tbl WHERE a = 1;
    **             SELECT a, b, c FROM tbl WHERE a = 1;
    */
    int nEq;
    int bInEst = 0;
    int nInMul = 1;
    int estBound = 100;
    int nBound = 0;               /* Number of range constraints seen */
    int bSort = 0;
    int bLookup = 0;
    WhereTerm *pTerm;             /* A single term of the WHERE clause */
#ifdef SQLITE_ENABLE_STAT2
    WhereTerm *pFirstTerm = 0;    /* First term matching the index */
#endif

    /* Determine the values of nEq and nInMul */
    for(nEq=0; nEq<pProbe->nColumn; nEq++){
................................................................................
      if( pTerm->eOperator & WO_IN ){
        Expr *pExpr = pTerm->pExpr;
        wsFlags |= WHERE_COLUMN_IN;
        if( ExprHasProperty(pExpr, EP_xIsSelect) ){
          /* "x IN (SELECT ...)":  Assume the SELECT returns 25 rows */
          nInMul *= 25;
          bInEst = 1;
        }else if( ALWAYS(pExpr->x.pList) ){
          /* "x IN (value, value, ...)" */
          nInMul *= pExpr->x.pList->nExpr + 1;
        }
      }else if( pTerm->eOperator & WO_ISNULL ){
        wsFlags |= WHERE_COLUMN_NULL;
      }
#ifdef SQLITE_ENABLE_STAT2
      if( nEq==0 && pProbe->aSample ) pFirstTerm = pTerm;
#endif
................................................................................
    }
#endif /* SQLITE_ENABLE_STAT2 */

    /* Adjust the number of rows and the cost downward to reflect rows
    ** that are excluded by range constraints.
    */
    nRow = (nRow * (double)estBound) / (double)100;


    /* Assume constant cost to access a row and logarithmic cost to
    ** do a binary search.  Hence, the initial cost is the number of output

    ** rows plus log2(table-size) times the number of binary searches.





    */

    if( pIdx && bLookup ){
      cost = nRow + (nInMul+nRow)*estLog(aiRowEst[0]);






    }else{
      cost = nRow + nInMul*estLog(aiRowEst[0]);





    }









    /* Add in the estimated cost of sorting the result.  This cost is expanded
    ** by a fudge factor of 3.0 to account for the fact that a sorting step 
    ** involves a write and is thus more expensive than a lookup step.
    */
    if( bSort ){
      cost += nRow*estLog(nRow)*(double)3;
................................................................................
        }else if( pTerm->eOperator & (WO_LT|WO_LE|WO_GT|WO_GE) ){
          if( nSkipRange ){
            /* Ignore the first nSkipRange range constraints since the index
            ** has already accounted for these */
            nSkipRange--;
          }else{
            /* Assume each additional range constraint reduces the result
            ** set size by a factor of 3 */




            nRow /= 3;
          }
        }else if( pTerm->eOperator!=WO_NOOP ){
          /* Any other expression lowers the output row count by half */
          nRow /= 2;
        }
      }







|
|
|







 







|
|







 







|




|







 







|







 







|
|
>
>
|










>
>







 







>




|




>
>







 







|
>
>







|
|







|
|
>
|
|
|

|
>
>




|
|
|
|

|
|







 







|

|







 







>

|
|
>
|
>
>
>
>
>

>
|
<
>
>
>
>
>
>
|
<
>
>
>
>
>
|
>
>
>
>
>
>
>
>







 







|
>
>
>
>







2417
2418
2419
2420
2421
2422
2423
2424
2425
2426
2427
2428
2429
2430
2431
2432
2433
....
2494
2495
2496
2497
2498
2499
2500
2501
2502
2503
2504
2505
2506
2507
2508
2509
....
2632
2633
2634
2635
2636
2637
2638
2639
2640
2641
2642
2643
2644
2645
2646
2647
2648
2649
2650
2651
....
2656
2657
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
....
2699
2700
2701
2702
2703
2704
2705
2706
2707
2708
2709
2710
2711
2712
2713
2714
2715
2716
2717
2718
2719
2720
2721
2722
2723
2724
2725
2726
2727
2728
2729
....
2733
2734
2735
2736
2737
2738
2739
2740
2741
2742
2743
2744
2745
2746
2747
2748
2749
2750
2751
2752
2753
2754
2755
2756
2757
2758
....
2768
2769
2770
2771
2772
2773
2774
2775
2776
2777
2778
2779
2780
2781
2782
2783
2784
2785
2786
2787
2788
2789
2790
2791
2792
2793
2794
2795
2796
2797
2798
2799
2800
2801
2802
2803
2804
2805
2806
2807
2808
2809
2810
2811
2812
2813
2814
2815
2816
2817
2818
2819
2820
2821
....
2826
2827
2828
2829
2830
2831
2832
2833
2834
2835
2836
2837
2838
2839
2840
2841
2842
....
2931
2932
2933
2934
2935
2936
2937
2938
2939
2940
2941
2942
2943
2944
2945
2946
2947
2948
2949
2950
2951

2952
2953
2954
2955
2956
2957
2958

2959
2960
2961
2962
2963
2964
2965
2966
2967
2968
2969
2970
2971
2972
2973
2974
2975
2976
2977
2978
2979
....
3020
3021
3022
3023
3024
3025
3026
3027
3028
3029
3030
3031
3032
3033
3034
3035
3036
3037
3038
** value of 1 indicates that the proposed range scan is expected to visit
** approximately 1/100th (1%) of the rows selected by the nEq equality
** constraints (if any). A return value of 100 indicates that it is expected
** that the range scan will visit every row (100%) selected by the equality
** constraints.
**
** In the absence of sqlite_stat2 ANALYZE data, each range inequality
** reduces the search space by 3/4ths.  Hence a single constraint (x>?)
** results in a return of 25 and a range constraint (x>? AND x<?) results
** in a return of 6.
*/
static int whereRangeScanEst(
  Parse *pParse,       /* Parsing & code generating context */
  Index *p,            /* The index containing the range-compared column; "x" */
  int nEq,             /* index into p->aCol[] of the range-compared column */
  WhereTerm *pLower,   /* Lower bound on the range. ex: "x>123" Might be NULL */
  WhereTerm *pUpper,   /* Upper bound on the range. ex: "x<455" Might be NULL */
................................................................................
#else
  UNUSED_PARAMETER(pParse);
  UNUSED_PARAMETER(p);
  UNUSED_PARAMETER(nEq);
#endif
  assert( pLower || pUpper );
  *piEst = 100;
  if( pLower && (pLower->wtFlags & TERM_VNULL)==0 ) *piEst /= 4;
  if( pUpper ) *piEst /= 4;
  return rc;
}

#ifdef SQLITE_ENABLE_STAT2
/*
** Estimate the number of rows that will be returned based on
** an equality constraint x=VALUE and where that VALUE occurs in
................................................................................
  sqlite3ValueFree(pVal);
  return rc;
}
#endif /* defined(SQLITE_ENABLE_STAT2) */


/*
** Find the best query plan for accessing a particular table.  Write the
** best query plan and its cost into the WhereCost object supplied as the
** last parameter.
**
** The lowest cost plan wins.  The cost is an estimate of the amount of
** CPU and disk I/O needed to process the requested result.
** Factors that influence cost include:
**
**    *  The estimated number of rows that will be retrieved.  (The
**       fewer the better.)
**
**    *  Whether or not sorting must occur.
**
................................................................................
** the SQL statement, then this function only considers plans using the 
** named index. If no such plan is found, then the returned cost is
** SQLITE_BIG_DBL. If a plan is found that uses the named index, 
** then the cost is calculated in the usual way.
**
** If a NOT INDEXED clause (pSrc->notIndexed!=0) was attached to the table 
** in the SELECT statement, then no indexes are considered. However, the 
** selected plan may still take advantage of the built-in rowid primary key
** index.
*/
static void bestBtreeIndex(
  Parse *pParse,              /* The parsing context */
  WhereClause *pWC,           /* The WHERE clause */
  struct SrcList_item *pSrc,  /* The FROM clause term to search */
  Bitmask notReady,           /* Mask of cursors not available for indexing */
................................................................................

  if( pSrc->pIndex ){
    /* An INDEXED BY clause specifies a particular index to use */
    pIdx = pProbe = pSrc->pIndex;
    wsFlagMask = ~(WHERE_ROWID_EQ|WHERE_ROWID_RANGE);
    eqTermMask = idxEqTermMask;
  }else{
    /* There is no INDEXED BY clause.  Create a fake Index object in local
    ** variable sPk to represent the rowid primary key index.  Make this
    ** fake index the first in a chain of Index objects with all of the real
    ** indices to follow */
    Index *pFirst;                  /* First of real indices on the table */
    memset(&sPk, 0, sizeof(Index));
    sPk.nColumn = 1;
    sPk.aiColumn = &aiColumnPk;
    sPk.aiRowEst = aiRowEstPk;
    sPk.onError = OE_Replace;
    sPk.pTable = pSrc->pTab;
    aiRowEstPk[0] = pSrc->pTab->nRowEst;
    aiRowEstPk[1] = 1;
    pFirst = pSrc->pTab->pIndex;
    if( pSrc->notIndexed==0 ){
      /* The real indices of the table are only considered if the
      ** NOT INDEXED qualifier is omitted from the FROM clause */
      sPk.pNext = pFirst;
    }
    pProbe = &sPk;
    wsFlagMask = ~(
        WHERE_COLUMN_IN|WHERE_COLUMN_EQ|WHERE_COLUMN_NULL|WHERE_COLUMN_RANGE
    );
    eqTermMask = WO_EQ|WO_IN;
................................................................................
  /* Loop over all indices looking for the best one to use
  */
  for(; pProbe; pIdx=pProbe=pProbe->pNext){
    const unsigned int * const aiRowEst = pProbe->aiRowEst;
    double cost;                /* Cost of using pProbe */
    double nRow;                /* Estimated number of rows in result set */
    int rev;                    /* True to scan in reverse order */
    double nSearch;             /* Estimated number of binary searches */
    int wsFlags = 0;
    Bitmask used = 0;

    /* The following variables are populated based on the properties of
    ** index being evaluated. They are then used to determine the expected
    ** cost and number of rows returned.
    **
    **  nEq: 
    **    Number of equality terms that can be implemented using the index.
    **    In other words, the number of initial fields in the index that
    **    are used in == or IN or NOT NULL constraints of the WHERE clause.
    **
    **  nInMul:  
    **    The "in-multiplier". This is an estimate of how many seek operations 
    **    SQLite must perform on the index in question. For example, if the 
    **    WHERE clause is:
    **
    **      WHERE a IN (1, 2, 3) AND b IN (4, 5, 6)
................................................................................
    **
    **    If there exists a WHERE term of the form "x IN (SELECT ...)", then 
    **    the sub-select is assumed to return 25 rows for the purposes of 
    **    determining nInMul.
    **
    **  bInEst:  
    **    Set to true if there was at least one "x IN (SELECT ...)" term used 
    **    in determining the value of nInMul.  Note that the RHS of the
    **    IN operator must be a SELECT, not a value list, for this variable
    **    to be true.
    **
    **  estBound:
    **    An estimate on the amount of the table that must be searched.  A
    **    value of 100 means the entire table is searched.  Range constraints
    **    might reduce this to a value less than 100 to indicate that only
    **    a fraction of the table needs searching.  In the absence of
    **    sqlite_stat2 ANALYZE data, a single inequality reduces the search
    **    space to 1/4rd its original size.  So an x>? constraint reduces
    **    estBound to 25.  Two constraints (x>? AND x<?) reduce estBound to 6.
    **
    **  bSort:   
    **    Boolean. True if there is an ORDER BY clause that will require an 
    **    external sort (i.e. scanning the index being evaluated will not 
    **    correctly order records).
    **
    **  bLookup: 
    **    Boolean. True if a table lookup is required for each index entry
    **    visited.  In other words, true if this is not a covering index.
    **    This is always false for the rowid primary key index of a table.
    **    For other indexes, it is true unless all the columns of the table
    **    used by the SELECT statement are present in the index (such an
    **    index is sometimes described as a covering index).
    **    For example, given the index on (a, b), the second of the following 
    **    two queries requires table b-tree lookups in order to find the value
    **    of column c, but the first does not because columns a and b are
    **    both available in the index.
    **
    **             SELECT a, b    FROM tbl WHERE a = 1;
    **             SELECT a, b, c FROM tbl WHERE a = 1;
    */
    int nEq;                      /* Number of == or IN terms matching index */
    int bInEst = 0;               /* True if "x IN (SELECT...)" seen */
    int nInMul = 1;               /* Number of distinct equalities to lookup */
    int estBound = 100;           /* Estimated reduction in search space */
    int nBound = 0;               /* Number of range constraints seen */
    int bSort = 0;                /* True if external sort required */
    int bLookup = 0;              /* True if not a covering index */
    WhereTerm *pTerm;             /* A single term of the WHERE clause */
#ifdef SQLITE_ENABLE_STAT2
    WhereTerm *pFirstTerm = 0;    /* First term matching the index */
#endif

    /* Determine the values of nEq and nInMul */
    for(nEq=0; nEq<pProbe->nColumn; nEq++){
................................................................................
      if( pTerm->eOperator & WO_IN ){
        Expr *pExpr = pTerm->pExpr;
        wsFlags |= WHERE_COLUMN_IN;
        if( ExprHasProperty(pExpr, EP_xIsSelect) ){
          /* "x IN (SELECT ...)":  Assume the SELECT returns 25 rows */
          nInMul *= 25;
          bInEst = 1;
        }else if( ALWAYS(pExpr->x.pList && pExpr->x.pList->nExpr) ){
          /* "x IN (value, value, ...)" */
          nInMul *= pExpr->x.pList->nExpr;
        }
      }else if( pTerm->eOperator & WO_ISNULL ){
        wsFlags |= WHERE_COLUMN_NULL;
      }
#ifdef SQLITE_ENABLE_STAT2
      if( nEq==0 && pProbe->aSample ) pFirstTerm = pTerm;
#endif
................................................................................
    }
#endif /* SQLITE_ENABLE_STAT2 */

    /* Adjust the number of rows and the cost downward to reflect rows
    ** that are excluded by range constraints.
    */
    nRow = (nRow * (double)estBound) / (double)100;
    if( nRow<1 ) nRow = 1;

    /* Assume constant cost to advance from one row to the next and
    ** logarithmic cost to do a binary search.  Hence, the initial cost
    ** is the number of output rows plus log2(table-size) times the
    ** number of binary searches.
    **
    ** Because fan-out on tables is so much higher than the fan-out on
    ** indices (because table btrees contain only integer keys in non-leaf
    ** nodes) we weight the cost of a table binary search as 1/10th the
    ** cost of an index binary search.
    */
    if( pIdx ){
      if( bLookup ){

        /* For an index lookup followed by a table lookup:
        **    nInMul index searches to find the start of each index range
        **  + nRow steps through the index
        **  + nRow table searches to lookup the table entry using the rowid
        */
        nSearch = nInMul + nRow/10;
      }else{

        /* For a covering index:
        **     nInMul binary searches to find the initial entry 
        **   + nRow steps through the index
        */
        nSearch = nInMul;
      }
    }else{
      /* For a rowid primary key lookup:
      **    nInMult binary searches to find the initial entry scaled by 1/10th
      **  + nRow steps through the table
      */
      nSearch = nInMul/10;
    }
    cost = nRow + nSearch*estLog(aiRowEst[0]);

    /* Add in the estimated cost of sorting the result.  This cost is expanded
    ** by a fudge factor of 3.0 to account for the fact that a sorting step 
    ** involves a write and is thus more expensive than a lookup step.
    */
    if( bSort ){
      cost += nRow*estLog(nRow)*(double)3;
................................................................................
        }else if( pTerm->eOperator & (WO_LT|WO_LE|WO_GT|WO_GE) ){
          if( nSkipRange ){
            /* Ignore the first nSkipRange range constraints since the index
            ** has already accounted for these */
            nSkipRange--;
          }else{
            /* Assume each additional range constraint reduces the result
            ** set size by a factor of 3.  Indexed range constraints reduce
            ** the search space by a larger factor: 4.  We make indexed range
            ** more selective intentionally because of the subjective 
            ** observation that indexed range constraints really are more
            ** selective in practice, on average. */
            nRow /= 3;
          }
        }else if( pTerm->eOperator!=WO_NOOP ){
          /* Any other expression lowers the output row count by half */
          nRow /= 2;
        }
      }

Changes to test/analyze2.test.

238
239
240
241
242
243
244

245
246
247
248

249
250
251
252
253
254
255
...
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
...
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
...
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
    execsql { INSERT INTO t3 VALUES($str, $str) }
  }
  execsql COMMIT
  execsql ANALYZE
} {}
do_test analyze2-4.2 {
  execsql { 

    SELECT tbl,idx,group_concat(sample,' ') 
    FROM sqlite_stat2 
    WHERE idx = 't3a' 
    GROUP BY tbl,idx

  }
} {t3 t3a {AfA bEj CEj dEj EEj fEj GEj hEj IEj jEj}}
do_test analyze2-4.3 {
  execsql { 
    SELECT tbl,idx,group_concat(sample,' ') 
    FROM sqlite_stat2 
    WHERE idx = 't3b' 
................................................................................
    DELETE FROM sqlite_stat2;
  }
  sqlite3 db test.db
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
} {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~110000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}
do_test analyze2-6.2.2 {
  db cache flush
  execsql ANALYZE
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
................................................................................
    DELETE FROM sqlite_master WHERE tbl_name = 'sqlite_stat1';
  }
  sqlite3 db test.db
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
} {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~110000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}
do_test analyze2-6.2.5 {
  execsql { 
    PRAGMA writable_schema = 1;
    DELETE FROM sqlite_master WHERE tbl_name = 'sqlite_stat2';
  }
  sqlite3 db test.db
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
} {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~110000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}
do_test analyze2-6.2.6 {
  execsql { 
    PRAGMA writable_schema = 1;
    INSERT INTO sqlite_master SELECT * FROM master;
  }
  sqlite3 db test.db
  execsql ANALYZE
................................................................................
  do_test analyze2-7.10 {
    incr_schema_cookie test.db
    execsql { SELECT * FROM sqlite_master } db1
    eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
          t5.a>1 AND t5.a<15 AND
          t6.a>1
    } db1
  } {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~2 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}

  db1 close
  db2 close
  sqlite3_enable_shared_cache $::enable_shared_cache
}

finish_test







>



|
>







 







|







 







|










|







 







|







238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
...
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
...
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
...
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
    execsql { INSERT INTO t3 VALUES($str, $str) }
  }
  execsql COMMIT
  execsql ANALYZE
} {}
do_test analyze2-4.2 {
  execsql { 
    PRAGMA automatic_index=OFF;
    SELECT tbl,idx,group_concat(sample,' ') 
    FROM sqlite_stat2 
    WHERE idx = 't3a' 
    GROUP BY tbl,idx;
    PRAGMA automatic_index=ON;
  }
} {t3 t3a {AfA bEj CEj dEj EEj fEj GEj hEj IEj jEj}}
do_test analyze2-4.3 {
  execsql { 
    SELECT tbl,idx,group_concat(sample,' ') 
    FROM sqlite_stat2 
    WHERE idx = 't3b' 
................................................................................
    DELETE FROM sqlite_stat2;
  }
  sqlite3 db test.db
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
} {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~60000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}
do_test analyze2-6.2.2 {
  db cache flush
  execsql ANALYZE
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
................................................................................
    DELETE FROM sqlite_master WHERE tbl_name = 'sqlite_stat1';
  }
  sqlite3 db test.db
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
} {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~60000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}
do_test analyze2-6.2.5 {
  execsql { 
    PRAGMA writable_schema = 1;
    DELETE FROM sqlite_master WHERE tbl_name = 'sqlite_stat2';
  }
  sqlite3 db test.db
  eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
        t5.a>1 AND t5.a<15 AND
        t6.a>1
  }
} {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~60000 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}
do_test analyze2-6.2.6 {
  execsql { 
    PRAGMA writable_schema = 1;
    INSERT INTO sqlite_master SELECT * FROM master;
  }
  sqlite3 db test.db
  execsql ANALYZE
................................................................................
  do_test analyze2-7.10 {
    incr_schema_cookie test.db
    execsql { SELECT * FROM sqlite_master } db1
    eqp { SELECT * FROM t5,t6 WHERE t5.rowid=t6.rowid AND 
          t5.a>1 AND t5.a<15 AND
          t6.a>1
    } db1
  } {0 0 0 {SEARCH TABLE t5 USING COVERING INDEX t5i (a>? AND a<?) (~1 rows)} 0 1 1 {SEARCH TABLE t6 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}}

  db1 close
  db2 close
  sqlite3_enable_shared_cache $::enable_shared_cache
}

finish_test

Changes to test/analyze3.test.

244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
    append t [lindex {a b c d e f g h i j} [expr ($i%10)]]
    execsql { INSERT INTO t1 VALUES($i, $t) }
  }
  execsql COMMIT
} {}
do_eqp_test analyze3-2.2 {
  SELECT count(a) FROM t1 WHERE b LIKE 'a%'
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (b>? AND b<?) (~55000 rows)}}
do_eqp_test analyze3-2.3 {
  SELECT count(a) FROM t1 WHERE b LIKE '%a'
} {0 0 0 {SCAN TABLE t1 (~500000 rows)}}

do_test analyze3-2.4 {
  sf_execsql { SELECT count(*) FROM t1 WHERE b LIKE 'a%' }
} {101 0 100}







|







244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
    append t [lindex {a b c d e f g h i j} [expr ($i%10)]]
    execsql { INSERT INTO t1 VALUES($i, $t) }
  }
  execsql COMMIT
} {}
do_eqp_test analyze3-2.2 {
  SELECT count(a) FROM t1 WHERE b LIKE 'a%'
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (b>? AND b<?) (~30000 rows)}}
do_eqp_test analyze3-2.3 {
  SELECT count(a) FROM t1 WHERE b LIKE '%a'
} {0 0 0 {SCAN TABLE t1 (~500000 rows)}}

do_test analyze3-2.4 {
  sf_execsql { SELECT count(*) FROM t1 WHERE b LIKE 'a%' }
} {101 0 100}

Changes to test/e_createtable.test.

1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
  1    "EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE b = 5" 
       {0 0 0 {SEARCH TABLE t1 USING INDEX sqlite_autoindex_t1_1 (b=?) (~1 rows)}}

  2    "EXPLAIN QUERY PLAN SELECT * FROM t2 ORDER BY b, c"
       {0 0 0 {SCAN TABLE t2 USING INDEX sqlite_autoindex_t2_1 (~1000000 rows)}}

  3    "EXPLAIN QUERY PLAN SELECT * FROM t2 WHERE b=10 AND c>10"
       {0 0 0 {SEARCH TABLE t2 USING INDEX sqlite_autoindex_t2_1 (b=? AND c>?) (~3 rows)}}
}

# EVIDENCE-OF: R-45493-35653 A CHECK constraint may be attached to a
# column definition or specified as a table constraint. In practice it
# makes no difference.
#
#   All the tests that deal with CHECK constraints below (4.11.* and 







|







1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
  1    "EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE b = 5" 
       {0 0 0 {SEARCH TABLE t1 USING INDEX sqlite_autoindex_t1_1 (b=?) (~1 rows)}}

  2    "EXPLAIN QUERY PLAN SELECT * FROM t2 ORDER BY b, c"
       {0 0 0 {SCAN TABLE t2 USING INDEX sqlite_autoindex_t2_1 (~1000000 rows)}}

  3    "EXPLAIN QUERY PLAN SELECT * FROM t2 WHERE b=10 AND c>10"
       {0 0 0 {SEARCH TABLE t2 USING INDEX sqlite_autoindex_t2_1 (b=? AND c>?) (~2 rows)}}
}

# EVIDENCE-OF: R-45493-35653 A CHECK constraint may be attached to a
# column definition or specified as a table constraint. In practice it
# makes no difference.
#
#   All the tests that deal with CHECK constraints below (4.11.* and 

Changes to test/eqp.test.

388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411

# EVIDENCE-OF: R-22253-05302 sqlite> EXPLAIN QUERY PLAN SELECT t1.*,
# t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2; 0|0|0|SEARCH TABLE t1
# USING COVERING INDEX i2 (a=? AND b>?) (~3 rows) 0|1|1|SCAN TABLE t2
# (~1000000 rows)
do_execsql_test 5.4.0 {CREATE TABLE t2(c, d)}
det 5.4.1 "SELECT t1.*, t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2" {
  0 0 0 {SEARCH TABLE t1 USING COVERING INDEX i2 (a=? AND b>?) (~3 rows)}
  0 1 1 {SCAN TABLE t2 (~1000000 rows)}
}

# EVIDENCE-OF: R-21040-07025 sqlite> EXPLAIN QUERY PLAN SELECT t1.*,
# t2.* FROM t2, t1 WHERE t1.a=1 AND t1.b>2; 0|0|1|SEARCH TABLE t1
# USING COVERING INDEX i2 (a=? AND b>?) (~3 rows) 0|1|0|SCAN TABLE t2
# (~1000000 rows)
det 5.5 "SELECT t1.*, t2.* FROM t2, t1 WHERE t1.a=1 AND t1.b>2" {
  0 0 1 {SEARCH TABLE t1 USING COVERING INDEX i2 (a=? AND b>?) (~3 rows)}
  0 1 0 {SCAN TABLE t2 (~1000000 rows)}
}

# EVIDENCE-OF: R-39007-61103 sqlite> CREATE INDEX i3 ON t1(b);
# sqlite> EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE a=1 OR b=2;
# 0|0|0|SEARCH TABLE t1 USING COVERING INDEX i2 (a=?) (~10 rows)
# 0|0|0|SEARCH TABLE t1 USING INDEX i3 (b=?) (~10 rows)







|








|







388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411

# EVIDENCE-OF: R-22253-05302 sqlite> EXPLAIN QUERY PLAN SELECT t1.*,
# t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2; 0|0|0|SEARCH TABLE t1
# USING COVERING INDEX i2 (a=? AND b>?) (~3 rows) 0|1|1|SCAN TABLE t2
# (~1000000 rows)
do_execsql_test 5.4.0 {CREATE TABLE t2(c, d)}
det 5.4.1 "SELECT t1.*, t2.* FROM t1, t2 WHERE t1.a=1 AND t1.b>2" {
  0 0 0 {SEARCH TABLE t1 USING COVERING INDEX i2 (a=? AND b>?) (~2 rows)}
  0 1 1 {SCAN TABLE t2 (~1000000 rows)}
}

# EVIDENCE-OF: R-21040-07025 sqlite> EXPLAIN QUERY PLAN SELECT t1.*,
# t2.* FROM t2, t1 WHERE t1.a=1 AND t1.b>2; 0|0|1|SEARCH TABLE t1
# USING COVERING INDEX i2 (a=? AND b>?) (~3 rows) 0|1|0|SCAN TABLE t2
# (~1000000 rows)
det 5.5 "SELECT t1.*, t2.* FROM t2, t1 WHERE t1.a=1 AND t1.b>2" {
  0 0 1 {SEARCH TABLE t1 USING COVERING INDEX i2 (a=? AND b>?) (~2 rows)}
  0 1 0 {SCAN TABLE t2 (~1000000 rows)}
}

# EVIDENCE-OF: R-39007-61103 sqlite> CREATE INDEX i3 ON t1(b);
# sqlite> EXPLAIN QUERY PLAN SELECT * FROM t1 WHERE a=1 OR b=2;
# 0|0|0|SEARCH TABLE t1 USING COVERING INDEX i2 (a=?) (~10 rows)
# 0|0|0|SEARCH TABLE t1 USING INDEX i3 (b=?) (~10 rows)

Changes to test/indexedby.test.

150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
# Test embedding an INDEXED BY in a CREATE VIEW statement. This block
# also tests that nothing bad happens if an index refered to by
# a CREATE VIEW statement is dropped and recreated.
#
do_execsql_test indexedby-5.1 {
  CREATE VIEW v2 AS SELECT * FROM t1 INDEXED BY i1 WHERE a > 5;
  EXPLAIN QUERY PLAN SELECT * FROM v2 
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?) (~330000 rows)}}
do_execsql_test indexedby-5.2 {
  EXPLAIN QUERY PLAN SELECT * FROM v2 WHERE b = 10 
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?) (~33000 rows)}}
do_test indexedby-5.3 {
  execsql { DROP INDEX i1 }
  catchsql { SELECT * FROM v2 }
} {1 {no such index: i1}}
do_test indexedby-5.4 {
  # Recreate index i1 in such a way as it cannot be used by the view query.
  execsql { CREATE INDEX i1 ON t1(b) }







|


|







150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
# Test embedding an INDEXED BY in a CREATE VIEW statement. This block
# also tests that nothing bad happens if an index refered to by
# a CREATE VIEW statement is dropped and recreated.
#
do_execsql_test indexedby-5.1 {
  CREATE VIEW v2 AS SELECT * FROM t1 INDEXED BY i1 WHERE a > 5;
  EXPLAIN QUERY PLAN SELECT * FROM v2 
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?) (~250000 rows)}}
do_execsql_test indexedby-5.2 {
  EXPLAIN QUERY PLAN SELECT * FROM v2 WHERE b = 10 
} {0 0 0 {SEARCH TABLE t1 USING INDEX i1 (a>?) (~25000 rows)}}
do_test indexedby-5.3 {
  execsql { DROP INDEX i1 }
  catchsql { SELECT * FROM v2 }
} {1 {no such index: i1}}
do_test indexedby-5.4 {
  # Recreate index i1 in such a way as it cannot be used by the view query.
  execsql { CREATE INDEX i1 ON t1(b) }

Changes to test/like.test.

703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
...
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
...
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
      INSERT INTO t10 VALUES(12,12,12,12,12,12);
      INSERT INTO t10 VALUES(123,123,123,123,123,123);
      INSERT INTO t10 VALUES(234,234,234,234,234,234);
      INSERT INTO t10 VALUES(345,345,345,345,345,345);
      INSERT INTO t10 VALUES(45,45,45,45,45,45);
    }
    count {
      SELECT a FROM t10 WHERE b LIKE '12%' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.2 {
    count {
      SELECT a FROM t10 WHERE c LIKE '12%' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.3 {
    count {
      SELECT a FROM t10 WHERE d LIKE '12%' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.4 {
    count {
      SELECT a FROM t10 WHERE e LIKE '12%' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.5 {
    count {
      SELECT a FROM t10 WHERE f LIKE '12%' ORDER BY a;
    }
  } {12 123 scan 3 like 0}
  do_test like-10.6 {
    count {
      SELECT a FROM t10 WHERE a LIKE '12%' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.10 {
    execsql {
      CREATE TABLE t10b(
        a INTEGER PRIMARY KEY,
        b INTEGER UNIQUE,
................................................................................
        d BLOB UNIQUE,
        e UNIQUE,
        f TEXT UNIQUE
      );
      INSERT INTO t10b SELECT * FROM t10;
    }
    count {
      SELECT a FROM t10b WHERE b GLOB '12*' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.11 {
    count {
      SELECT a FROM t10b WHERE c GLOB '12*' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.12 {
    count {
      SELECT a FROM t10b WHERE d GLOB '12*' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.13 {
    count {
      SELECT a FROM t10b WHERE e GLOB '12*' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.14 {
    count {
      SELECT a FROM t10b WHERE f GLOB '12*' ORDER BY a;
    }
  } {12 123 scan 3 like 0}
  do_test like-10.15 {
    count {
      SELECT a FROM t10b WHERE a GLOB '12*' ORDER BY a;
    }
  } {12 123 scan 5 like 6}
}

# LIKE and GLOB where the default collating sequence is not appropriate
# but an index with the appropriate collating sequence exists.
#
................................................................................
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd nosort t11 *}
do_test like-11.3 {
  queryplan {
    PRAGMA case_sensitive_like=OFF;
    CREATE INDEX t11b ON t11(b);
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd ABC ABCD sort {} t11b}
do_test like-11.4 {
  queryplan {
    PRAGMA case_sensitive_like=ON;
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd nosort t11 *}
do_test like-11.5 {
  queryplan {
    PRAGMA case_sensitive_like=OFF;
    DROP INDEX t11b;
    CREATE INDEX t11bnc ON t11(b COLLATE nocase);
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd ABC ABCD sort {} t11bnc}
do_test like-11.6 {
  queryplan {
    CREATE INDEX t11bb ON t11(b COLLATE binary);
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd ABC ABCD sort {} t11bnc}
do_test like-11.7 {
  queryplan {
    PRAGMA case_sensitive_like=ON;
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd sort {} t11bb}
do_test like-11.8 {
  queryplan {
    PRAGMA case_sensitive_like=OFF;
    SELECT b FROM t11 WHERE b GLOB 'abc*' ORDER BY a;
  }
} {abc abcd sort {} t11bb}
do_test like-11.9 {
  queryplan {
    CREATE INDEX t11cnc ON t11(c COLLATE nocase);
    CREATE INDEX t11cb ON t11(c COLLATE binary);
    SELECT c FROM t11 WHERE c LIKE 'abc%' ORDER BY a;
  }
} {abc abcd ABC ABCD sort {} t11cnc}
do_test like-11.10 {
  queryplan {
    SELECT c FROM t11 WHERE c GLOB 'abc*' ORDER BY a;
  }
} {abc abcd sort {} t11cb}


finish_test







|




|




|




|




|




|







 







|




|




|




|




|




|







 







|













|





|





|





|






|




|





703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
...
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
...
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
      INSERT INTO t10 VALUES(12,12,12,12,12,12);
      INSERT INTO t10 VALUES(123,123,123,123,123,123);
      INSERT INTO t10 VALUES(234,234,234,234,234,234);
      INSERT INTO t10 VALUES(345,345,345,345,345,345);
      INSERT INTO t10 VALUES(45,45,45,45,45,45);
    }
    count {
      SELECT a FROM t10 WHERE b LIKE '12%' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.2 {
    count {
      SELECT a FROM t10 WHERE c LIKE '12%' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.3 {
    count {
      SELECT a FROM t10 WHERE d LIKE '12%' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.4 {
    count {
      SELECT a FROM t10 WHERE e LIKE '12%' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.5 {
    count {
      SELECT a FROM t10 WHERE f LIKE '12%' ORDER BY +a;
    }
  } {12 123 scan 3 like 0}
  do_test like-10.6 {
    count {
      SELECT a FROM t10 WHERE a LIKE '12%' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.10 {
    execsql {
      CREATE TABLE t10b(
        a INTEGER PRIMARY KEY,
        b INTEGER UNIQUE,
................................................................................
        d BLOB UNIQUE,
        e UNIQUE,
        f TEXT UNIQUE
      );
      INSERT INTO t10b SELECT * FROM t10;
    }
    count {
      SELECT a FROM t10b WHERE b GLOB '12*' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.11 {
    count {
      SELECT a FROM t10b WHERE c GLOB '12*' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.12 {
    count {
      SELECT a FROM t10b WHERE d GLOB '12*' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.13 {
    count {
      SELECT a FROM t10b WHERE e GLOB '12*' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
  do_test like-10.14 {
    count {
      SELECT a FROM t10b WHERE f GLOB '12*' ORDER BY +a;
    }
  } {12 123 scan 3 like 0}
  do_test like-10.15 {
    count {
      SELECT a FROM t10b WHERE a GLOB '12*' ORDER BY +a;
    }
  } {12 123 scan 5 like 6}
}

# LIKE and GLOB where the default collating sequence is not appropriate
# but an index with the appropriate collating sequence exists.
#
................................................................................
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd nosort t11 *}
do_test like-11.3 {
  queryplan {
    PRAGMA case_sensitive_like=OFF;
    CREATE INDEX t11b ON t11(b);
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a;
  }
} {abc abcd ABC ABCD sort {} t11b}
do_test like-11.4 {
  queryplan {
    PRAGMA case_sensitive_like=ON;
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY a;
  }
} {abc abcd nosort t11 *}
do_test like-11.5 {
  queryplan {
    PRAGMA case_sensitive_like=OFF;
    DROP INDEX t11b;
    CREATE INDEX t11bnc ON t11(b COLLATE nocase);
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a;
  }
} {abc abcd ABC ABCD sort {} t11bnc}
do_test like-11.6 {
  queryplan {
    CREATE INDEX t11bb ON t11(b COLLATE binary);
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a;
  }
} {abc abcd ABC ABCD sort {} t11bnc}
do_test like-11.7 {
  queryplan {
    PRAGMA case_sensitive_like=ON;
    SELECT b FROM t11 WHERE b LIKE 'abc%' ORDER BY +a;
  }
} {abc abcd sort {} t11bb}
do_test like-11.8 {
  queryplan {
    PRAGMA case_sensitive_like=OFF;
    SELECT b FROM t11 WHERE b GLOB 'abc*' ORDER BY +a;
  }
} {abc abcd sort {} t11bb}
do_test like-11.9 {
  queryplan {
    CREATE INDEX t11cnc ON t11(c COLLATE nocase);
    CREATE INDEX t11cb ON t11(c COLLATE binary);
    SELECT c FROM t11 WHERE c LIKE 'abc%' ORDER BY +a;
  }
} {abc abcd ABC ABCD sort {} t11cnc}
do_test like-11.10 {
  queryplan {
    SELECT c FROM t11 WHERE c GLOB 'abc*' ORDER BY +a;
  }
} {abc abcd sort {} t11cb}


finish_test

Changes to test/minmax3.test.

48
49
50
51
52
53
54

55
56
57
58
59
60
61
    INSERT INTO t1 VALUES('1', 'I',   'one');
    INSERT INTO t1 VALUES('2', 'IV',  'four');
    INSERT INTO t1 VALUES('2', NULL,  'three');
    INSERT INTO t1 VALUES('2', 'II',  'two');
    INSERT INTO t1 VALUES('2', 'V',   'five');
    INSERT INTO t1 VALUES('3', 'VI',  'six');
    COMMIT;

  }
} {}
do_test minmax3-1.1.1 {
  # Linear scan.
  count { SELECT max(y) FROM t1 WHERE x = '2'; }
} {V 5}
do_test minmax3-1.1.2 {







>







48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
    INSERT INTO t1 VALUES('1', 'I',   'one');
    INSERT INTO t1 VALUES('2', 'IV',  'four');
    INSERT INTO t1 VALUES('2', NULL,  'three');
    INSERT INTO t1 VALUES('2', 'II',  'two');
    INSERT INTO t1 VALUES('2', 'V',   'five');
    INSERT INTO t1 VALUES('3', 'VI',  'six');
    COMMIT;
    PRAGMA automatic_index=OFF;
  }
} {}
do_test minmax3-1.1.1 {
  # Linear scan.
  count { SELECT max(y) FROM t1 WHERE x = '2'; }
} {V 5}
do_test minmax3-1.1.2 {

Changes to test/where3.test.

221
222
223
224
225
226
227
228
229
230

231
232
233
234
235
236
237
238
239
240
241
242
  CREATE TABLE t301(a INTEGER PRIMARY KEY,b,c);
  CREATE INDEX t301c ON t301(c);
  INSERT INTO t301 VALUES(1,2,3);
  CREATE TABLE t302(x, y);
  ANALYZE;
  explain query plan SELECT * FROM t302, t301 WHERE t302.x=5 AND t301.a=t302.y;
} {
  0 0 0 {SCAN TABLE t302 (~0 rows)} 
  0 1 1 {SEARCH TABLE t301 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}
}

do_execsql_test where3-3.1 {
  explain query plan
  SELECT * FROM t301, t302 WHERE t302.x=5 AND t301.a=t302.y;
} {
  0 0 1 {SCAN TABLE t302 (~0 rows)} 
  0 1 0 {SEARCH TABLE t301 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}
}

# Verify that when there are multiple tables in a join which must be
# full table scans that the query planner attempts put the table with
# the fewest number of output rows as the outer loop.
#







|


>




|







221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
  CREATE TABLE t301(a INTEGER PRIMARY KEY,b,c);
  CREATE INDEX t301c ON t301(c);
  INSERT INTO t301 VALUES(1,2,3);
  CREATE TABLE t302(x, y);
  ANALYZE;
  explain query plan SELECT * FROM t302, t301 WHERE t302.x=5 AND t301.a=t302.y;
} {
  0 0 0 {SCAN TABLE t302 (~1 rows)} 
  0 1 1 {SEARCH TABLE t301 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}
}
exit
do_execsql_test where3-3.1 {
  explain query plan
  SELECT * FROM t301, t302 WHERE t302.x=5 AND t301.a=t302.y;
} {
  0 0 1 {SCAN TABLE t302 (~1 rows)} 
  0 1 0 {SEARCH TABLE t301 USING INTEGER PRIMARY KEY (rowid=?) (~1 rows)}
}

# Verify that when there are multiple tables in a join which must be
# full table scans that the query planner attempts put the table with
# the fewest number of output rows as the outer loop.
#

Changes to test/where9.test.

468
469
470
471
472
473
474
475
476
477
478
479
480
481
482

  # Likewise, inequalities in an AND are preferred over inequalities in
  # an OR.
  #
  do_execsql_test where9-5.3 {
    EXPLAIN QUERY PLAN SELECT a FROM t1 WHERE b>1000 AND (c>=31031 OR d IS NULL)
  } {
    0 0 0 {SEARCH TABLE t1 USING INDEX t1b (b>?) (~165000 rows)}
  }
}

############################################################################
# Make sure OR-clauses work correctly on UPDATE and DELETE statements.

do_test where9-6.2.1 {







|







468
469
470
471
472
473
474
475
476
477
478
479
480
481
482

  # Likewise, inequalities in an AND are preferred over inequalities in
  # an OR.
  #
  do_execsql_test where9-5.3 {
    EXPLAIN QUERY PLAN SELECT a FROM t1 WHERE b>1000 AND (c>=31031 OR d IS NULL)
  } {
    0 0 0 {SEARCH TABLE t1 USING INDEX t1b (b>?) (~125000 rows)}
  }
}

############################################################################
# Make sure OR-clauses work correctly on UPDATE and DELETE statements.

do_test where9-6.2.1 {